Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer

PCDH11X mutation as a potential biomarker for immune checkpoint therapies in lung adenocarcinoma

Immune checkpoint inhibitors (ICIs) have achieved impressive success in lung adenocarcinoma (LUAD). However, the response to ICIs varies among patients, and predictive biomarkers are urgently needed. PCDH11X is frequently mutated in LUAD, while its role in ICI treatment is unclear. In this study, we curated genomic and clinical data of 151 LUAD patients receiving ICIs from three independent cohorts. Relations between PCDH11X and treatment outcomes of ICIs were examined. A melanoma cohort collected from five published studies, a pan-cancer cohort, and non-ICI-treated TCGA-LUAD cohort were also examined to investigate whether PCDH11X mutation is a specific predictive biomarker for LUAD ICI treatment. Among the three ICI-treated LUAD cohorts, PCDH11X mutation (PCDH11X-MUT) was associated with better clinical response compared to wild-type PCDH11X (PCDH11X-WT). While in ICI-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and the non-ICI-treated TCGA-LUAD cohort, no significant differences in overall survival (OS) were observed between the PCDH11X-MUT and PCDH11X-WT groups. PCDH11X mutation was associated with increased PD-L1 expression, tumor mutation burden (TMB), neoantigen load, DNA damage repair (DDR) mutations, and hot tumor microenvironment in TCGA-LUAD cohort. Our findings suggested that the PCDH11X mutation might serve as a specific biomarker to predict the efficacy of ICIs for LUAD patients. Considering the relatively small sample size of ICI-treated cohorts, future research with larger cohorts and prospective clinical trials will be essential for validating and further exploring the role of PCDH11X mutation in the context of immunotherapy outcomes in LUAD. KEY MESSAGES: PCDH11X mutation is associated with better clinical response compared to wild type PCDH11X in three ICIs-treated LUAD cohorts. In ICIs-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and non-ICIs-treated TCGA-LUAD cohorts PCDH11X mutation is not associated with better clinical response, suggesting PCDH11X mutation might be a specific biomarker to predict the efficacy of ICIs treatment for LUAD patients. PCDH11X mutation is associated with increased PD-L1 expression, tumor mutation burden, and neoantigen load in TCGA-LUAD cohort. PCDH11X mutation is associated with hot tumor microenvironment in TCGA-LUAD cohort.

Understanding the immunosuppressive microenvironment of glioma: mechanistic insights and clinical perspectives

Glioblastoma (GBM), the predominant and primary malignant intracranial tumor, poses a formidable challenge due to its immunosuppressive microenvironment, thereby confounding conventional therapeutic interventions. Despite the established treatment regimen comprising surgical intervention, radiotherapy, temozolomide administration, and the exploration of emerging modalities such as immunotherapy and integration of medicine and engineering technology therapy, the efficacy of these approaches remains constrained, resulting in suboptimal prognostic outcomes. In recent years, intensive scrutiny of the inhibitory and immunosuppressive milieu within GBM has underscored the significance of cellular constituents of the GBM microenvironment and their interactions with malignant cells and neurons. Novel immune and targeted therapy strategies have emerged, offering promising avenues for advancing GBM treatment. One pivotal mechanism orchestrating immunosuppression in GBM involves the aggregation of myeloid-derived suppressor cells (MDSCs), glioma-associated macrophage/microglia (GAM), and regulatory T cells (Tregs). Among these, MDSCs, though constituting a minority (4-8%) of CD45+ cells in GBM, play a central component in fostering immune evasion and propelling tumor progression, angiogenesis, invasion, and metastasis. MDSCs deploy intricate immunosuppressive mechanisms that adapt to the dynamic tumor microenvironment (TME). Understanding the interplay between GBM and MDSCs provides a compelling basis for therapeutic interventions. This review seeks to elucidate the immune regulatory mechanisms inherent in the GBM microenvironment, explore existing therapeutic targets, and consolidate recent insights into MDSC induction and their contribution to GBM immunosuppression. Additionally, the review comprehensively surveys ongoing clinical trials and potential treatment strategies, envisioning a future where targeting MDSCs could reshape the immune landscape of GBM. Through the synergistic integration of immunotherapy with other therapeutic modalities, this approach can establish a multidisciplinary, multi-target paradigm, ultimately improving the prognosis and quality of life in patients with GBM.

Characterization of zinc finger protein 536, a neuroendocrine regulator, using pan-cancer analysis

BACKGROUND

Previous studies suggested that zinc finger protein 536 (ZNF536) was abundant in the central brain and regulated neuronal differentiation. However, the role of ZNF536 in cancer has remained unclear.

METHODS

ZNF536 mutation, copy number alteration, DNA methylation, and RNA expression were explored using public portals. Data from The Cancer Genome Atlas (TCGA) were utilized to analyze pathways and tumor microenvironment (TME), with a focus on prognosis in both TCGA and immunotherapy pan-cancer cohorts. Methylated ZNF536 from small cell lung cancer (SCLC) cell lines were utilized to train with probes for conducting enrichment analysis. Single-cell RNA profile demonstrated the sublocalization and co-expression of ZNF536, and validated its targets by qPCR.

RESULTS

Genetic alterations in ZNF536 were found to be high-frequency and a single sample could harbor different variations. ZNF536 at chromosome 19q12 exerted a bypass effect on CCNE1, supported by CRISPR data. For lung cancer, ZNF536 mutation was associated with longer survival in primary lung adenocarcinoma (LUAD), but its prognosis was poor in metastatic LUAD and SCLC. Importantly, ZNF536 mutation and amplification had opposite prognoses in Stand Up To Cancer-Mark Foundation (SU2C-MARK) LUAD cohort. ZNF536 mutation altered the patterns of genomic alterations in tumors, and had distinct impacts on the signaling pathways and TME compared to ZNF536 amplification. Additionally, ZNF536 expression was predominantly in endocrine tumors and brain tissues. High-dimensional analysis supported this finding and further revealed regulators of ZNF536. Considering that the methylation of ZNF536 was involved in the synaptic pathway associated with neuroendocrine neoplasms, demonstrating both diagnostic and prognostic value. Moreover, we experimentally verified ZNF536 upregulated neuroendocrine markers.

CONCLUSIONS

Our results showed that ZNF536 alterations in cancer, including variations in copy number, mutation, and methylation. We proved the involvement of ZNF536 in neuroendocrine regulation, and identified highly altered ZNF536 as a potential biomarker for immunotherapy.

Targeting tumorous Circ-E-Cadherinencoded C-E-Cad inhibits the recruitment and function of breast cancer-associated myeloid-derived suppressor cells

We previously demonstrated that the C-E-cad protein encoded by circ-E-cadherin promotes the self-renewal of glioma stem cells. The expression pattern of C-E-cad in breast cancer and its potential function in the tumor microenvironment are unclear. The expression of circ-E-cadherin and C-E-cad was detected in breast cancer specimens. The influence of C-E-cad expression on MDSCs was assessed using FACS and in vivo tumorigenesis experiments. The synergistic effect of anti-C-E-cad and anti-PD-1 antibodies was validated in vivo. circ-E-cadherin and the encoded protein C-E-cad were found to be upregulated in breast cancer vs. normal samples. C-E-cad promotes the recruitment of MDSCs, especially PMN-MDSCs. C-E-cad activates EGFR signaling in tumor cells and promotes the transcription of CXCL8; moreover, C-E-cad binds to MDSCs and maintains glycolysis in PMN-MDSCs. Targeting C-E-cad enhanced anti-PD-1 efficiency. Our data suggested that C-E-cad is markedly overexpressed in breast cancer and promotes MDSC recruitment and survival. Targeting C-E-cad increases the efficacy of immune checkpoint inhibitor therapy.

Identification of a risk score model based on tertiary lymphoid structure-related genes for predicting immunotherapy efficacy in non-small cell lung cancer

BACKGROUND

Tertiary lymphoid structures (TLSs) affect the prognosis and efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC), but the underlying mechanisms are not well understood.

METHODS

TLSs were identified and categorized online from the Cancer Digital Slide Archive (CDSA). Overall survival (OS) and disease-free survival (DFS) were analyzed. GSE111414 and GSE136961 datasets were downloaded from the GEO database. GSVA, GO and KEGG were used to explore the signaling pathways. Immune cell infiltration was analyzed by xCell, ssGSEA and MCP-counter. The analysis of WGCNA, Lasso and multivariate cox regression were conducted to develop a gene risk score model based on the SU2C-MARK cohort.

RESULTS

TLS-positive was a protective factor for OS according to multivariate cox regression analysis (p = 0.029). Both the TLS-positive and TLS-mature groups exhibited genes enrichment in immune activation pathways. The TLS-mature group showed more activated dendritic cell infiltration than the TLS-immature group. We screened TLS-related genes using WGCNA. Lasso and multivariate cox regression analysis were used to construct a five-genes (RGS8, RUF4, HLA-DQB2, THEMIS, and TRBV12-5) risk score model, the progression free survival (PFS) and OS of patients in the low-risk group were markedly superior to those in the high-risk group (p < 0.0001; p = 0.0015, respectively). Calibration and ROC curves indicated that the combined model with gene risk score and clinical features could predict the PFS of patients who have received immunotherapy more accurately than a single clinical factor.

CONCLUSIONS

Our data suggested a pivotal role of TLSs formation in survival outcome and immunotherapy response of NSCLC patients. Tumors with mature TLS formation showed more activated immune microenvironment. In addition, the model constructed by TLS-related genes could predict the response to immunotherapy and is meaningful for clinical decision-making.

Redoxhigh phenotype mediated by KEAP1/STK11/SMARCA4/NRF2 mutations diminishes tissue-resident memory CD8+ T cells and attenuates the efficacy of immunotherapy in lung adenocarcinoma

Metabolism reprogramming within the tumor microenvironment (TME) can have a profound impact on immune cells. Identifying the association between metabolic phenotypes and immune cells in lung adenocarcinoma (LUAD) may reveal mechanisms of resistance to immune checkpoint inhibitors (ICIs). Metabolic phenotypes were classified by expression of metabolic genes. Somatic mutations and transcriptomic features were compared across the different metabolic phenotypes. The metabolic phenotype of LUAD is predominantly determined by reductase-oxidative activity and is divided into two categories: redoxhigh LUAD and redoxlow LUAD. Genetically, redoxhigh LUAD is mainly driven by mutations in KEAP1, STK11, NRF2, or SMARCA4. These mutations are more prevalent in redoxhigh LUAD (72.5%) compared to redoxlow LUAD (17.4%), whereas EGFR mutations are more common in redoxlow LUAD (19.0% vs. 0.7%). Single-cell RNA profiling of pre-treatment and post-treatment samples from patients receiving neoadjuvant chemoimmunotherapy revealed that tissue-resident memory CD8+ T cells are responders to ICIs. However, these cells are significantly reduced in redoxhigh LUAD. The redoxhigh phenotype is primarily attributed to tumor cells and is positively associated with mTORC1 signaling. LUAD with the redoxhigh phenotype demonstrates a lower response rate (39.1% vs. 70.8%, p = 0.001), shorter progression-free survival (3.3 vs. 14.6 months, p = 0.004), and overall survival (12.1 vs. 31.2 months, p = 0.022) when treated with ICIs. The redoxhigh phenotype in LUAD is predominantly driven by mutations in KEAP1, STK11, NRF2, and SMARCA4. This phenotype diminishes the number of tissue-resident memory CD8+ T cells and attenuates the efficacy of ICIs.

EGFR Oncogenic Mutations in NSCLC Impair Macrophage Phagocytosis and Mediate Innate Immune Evasion Through Up-Regulation of CD47

INTRODUCTION

EGFR-mutated NSCLC is characterized by an immunosuppressive microenvironment that confers limited clinical effectiveness to anti-PD-1 or PD-L1 antibodies. Despite the discouraging outcomes of immunotherapy, novel immune checkpoints are constantly emerging, among which the specific vulnerability for therapeutic intervention in the context of EGFR-mutated NSCLC remains unresolved.

METHODS

Data sets of patient- and cell line-levels were used for screening and mutual validation of association between EGFR mutation and a panel of immune checkpoint-related genes. Regulatory mechanism was elucidated through in vitro manipulation of EGFR signaling pathway and evaluated by immunoblot analysis, quantitative polymerase chain reaction, flow cytometry, immunofluorescence staining, and chromatin immunoprecipitation. In vivo investigation of different therapeutic strategies were conducted using both immunocompetent and immunodeficient mouse models.

RESULTS

Among all screened immune checkpoints, CD47 emerged as the candidate most relevant to EGFR activation. Mechanistically, EGFR mutation constitutively activated downstream ERK and AKT pathways to respectively up-regulate the transcriptional factors c-Myc and NF-κB, both of which structurally bound to the promotor region of CD47 and actively transcribed this "don't eat me" signal. Impaired macrophage phagocytosis was observed on introduction of EGFR-sensitizing mutations in NSCLC cell line models, whereas CD47 blockade restored the phagocytic capacity and augmented tumor cell killing in both in vitro and in vivo models. Remarkably, the combination of anti-CD47 antibody with EGFR tyrosine kinase inhibitor revealed an additive antitumor activity compared with monotherapy of either antitumor agent in both immunocompetent and adaptive immunity-deficient mouse models.

CONCLUSIONS

EGFR-sensitizing mutation facilitates NSCLC's escape from innate immune attack through up-regulating CD47. Combination therapy incorporating CD47 blockade holds substantial promise for clinical translation in developing more effective therapeutic approaches against EGFR-mutant NSCLC.

Tumor mutational burden for the prediction of PD-(L)1 blockade efficacy in cancer: challenges and opportunities

Tumor mutational burden (TMB) is a biomarker that measures the number of somatic mutations in a tumor's genome. TMB has emerged as a predictor of response to immune checkpoint inhibitors (ICIs) in various cancer types, and several studies have shown that patients with high TMB have better outcomes when treated with programmed death-ligand 1-based therapies. Recently, the Food and Drug Administration has approved TMB as a companion diagnostic for the use of pembrolizumab in solid tumors. However, despite its potential, the use of TMB as a biomarker for immunotherapy efficacy is limited by several factors. Here we review the limitations of TMB in predicting immunotherapy outcomes in patients with cancer and discuss potential strategies to optimize its use in the clinic.

Objective Analysis and Clinical Significance of the Spatial Tumor-Infiltrating Lymphocyte Patterns in Non-Small Cell Lung Cancer

PURPOSE

The spatial arrangement of lymphocytes in the tumor bed (e.g., immune infiltrated, immune excluded, immune desert) is expected to reflect distinct immune evasion mechanisms and to associate with immunotherapy outcomes. However, data supporting these associations are scant and limited by the lack of a clear definition for lymphocyte infiltration patterns and the subjective nature of pathology-based approaches.

EXPERIMENTAL DESIGN

We used multiplexed immunofluorescence to study major tumor-infiltrating lymphocyte (TIL) subsets with single-cell resolution in baseline whole-tissue section samples from NSCLC patients treated with immune checkpoint inhibitors (ICI). The spatial TIL patterns were analyzed using a qualitative pathologist-based approach, and an objective analysis of TIL density ratios in tumor/stromal tissues. The association of spatial patterns with outcomes was studied for different TIL markers.

RESULTS

The analysis of CD8+ TIL patterns using qualitative assessment identified prominent limitations including the presence of a broad spectrum of phenotypes within most tumors and limited association with outcomes. The utilization of an objective method to classify NSCLCs showed the existence of at least three subgroups with partial overlap with those defined using visual patterns. Using this strategy, a subset of cases with "immune excluded-like" tumors showed prominently worse outcomes, suggesting reduced sensitivity to ICI; however, these results need to be validated. The analysis for other TIL subsets showed different results, underscoring the relevance of the marker selected for spatial TIL pattern evaluation and opportunities for market integration.

CONCLUSIONS

Our results identified major challenges associated with the qualitative spatial TIL pattern evaluation. We devised a novel objective strategy to overcome some of these limitations that has strong biomarker potential.

Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is often the only source of tumor tissue from patients with advanced, inoperable lung cancer. EBUS-TBNA aspirates are used for the diagnosis, staging, and genomic testing to inform therapy options. Here we extracted DNA and RNA from 220 EBUS-TBNA aspirates to evaluate their suitability for whole genome (WGS), whole exome (WES), and comprehensive panel sequencing. For a subset of 40 cases, the same nucleic acid extraction was sequenced using WGS, WES, and the TruSight Oncology 500 assay. Genomic features were compared between sequencing platforms and compared with those reported by clinical testing. A total of 204 aspirates (92.7%) had sufficient DNA (100 ng) for comprehensive panel sequencing, and 109 aspirates (49.5%) had sufficient material for WGS. Comprehensive sequencing platforms detected all seven clinically reported tier 1 actionable mutations, an additional three (7%) tier 1 mutations, six (15%) tier 2-3 mutations, and biomarkers of potential immunotherapy benefit (tumor mutation burden and microsatellite instability). As expected, WGS was more suited for the detection and discovery of emerging novel biomarkers of treatment response. WGS could be performed in half of all EBUS-TBNA aspirates, which points to the enormous potential of EBUS-TBNA as source material for large, well-curated discovery-based studies for novel and more effective predictors of treatment response. Comprehensive panel sequencing is possible in the vast majority of fresh EBUS-TBNA aspirates and enhances the detection of actionable mutations over current clinical testing.

High-resolution transcriptomics analysis of CXCL13+ EPSTI1+ CDK1+ cells with a specific focus on lung adenocarcinoma

Background

Programmed cell death ligand 1 (PD-L1) blocking therapy has transformed the treatment of lung adenocarcinoma (LUAD), which has significantly changed the landscape of immunotherapy. We aimed to explore specific cell subpopulations to understand tumor progression and identify markers of response to PD-L1 blocking therapy.

Methods

Bulk, fluorescence-activated cell sorting (FACS), and single-cell RNA (scRNA) sequencing were used to profile CXCL13, EPSTI1, and CDK1. The gene set variation analysis (GSVA) R package was utilized for score calculation, and prognostic analyses included receiver operating characteristic (ROC) curves, Cox proportional hazard models, and meta-analysis. Additionally, we analyzed tumor microenvironment (TME), genomics, compound perturbations, and clinical indicators. The high-dimensional analysis captured the intrinsic characteristics of the subpopulation. Furthermore, subpopulation differential genes were used for enrichment analysis of transcription factors and compounds.

Results

Literature and website analyses supported the essential role of CXCL13, CDK1, and EPSTI1 in immunotherapy. This led us to focus specifically on LUAD by representing a pan-cancer profile of immune-sensitive genes. Logically, the high-characteristic population may consist of samples positive for CXCL13, EPSTI1, and CDK1. The three-gene signature was a favorable indicator of immunotherapy response in the Stand Up to Cancer-Mark Foundation (SU2C-MARK) LUAD cohort but showed a poor prognosis before treatment in the Lung Cancer Explorer (LCE) database. Further mechanistic exploration revealed specific mutations associated with the three-gene signature in SU2C-MARK LUAD, such as STK11. In The Cancer Genome Atlas (TCGA)-LUAD cohort, the high-scoring group exhibited a higher tumor mutational burden (TMB) and global methylation but a lower fraction genome altered (FGA) and estimated tumor purity. Moreover, dasatinib demonstrated sensitivity in the high-scoring group. The co-localization of the CXCL13, EPSTI1, and CDK1 subpopulation was validated through spatial transcriptome and immunohistochemical databases. Assessment of the subpopulation depicted high-resolution intercellular communication. Maintenance of specific pathways, such as TNF, CD74, and CD44, contributed to immunotherapy sensitivity. Finally, the subpopulation-enriched targets and drugs were confirmed through ConnectivityMap (CMAP) analysis and multi-omics, respectively.

Conclusions

In this study, positive samples for CXCL13, EPSTI1, and CDK1 exhibited poor prognostic significance in treatment-naïve LUAD cases but demonstrated benefits from PD-L1 blockade and dasatinib therapies.

Genetic insights into carbohydrate sulfotransferase 8 and its impact on the immunotherapy efficacy of cancer

Immune checkpoint blockade (ICB) is a promising therapy for solid tumors, but its effectiveness depends on biomarkers that are not precise. Here, we utilized genome-wide association study to investigate the association between genetic variants and tumor mutation burden to interpret ICB response. We identified 16 variants (p < 5 × 10-8) probed to 17 genes on 9 chromosomes. Subsequent analysis of one of the most significant loci in 19q13.11 suggested that the rs111308825 locus at the enhancer is causal, as its A allele impairs KLF2 binding, leading to lower carbohydrate sulfotransferase 8 (CHST8) expression. Breast cancer cells expressing CHST8 suppress T cell activation, and Chst8 loss attenuates tumor growth in a syngeneic mouse model. Further investigation revealed that programmed death-ligand 1 (PD-L1) and its homologs could be sulfated by CHST8, resulting in M2-like macrophage enrichment in the tumor microenvironment. Finally, we confirmed that low-CHST8 tumors have better ICB response, supporting the genetic effect and clinical value of rs111308825 for ICB efficacy prediction.

T proliferating cells derived autophagy signature associated with prognosis and immunotherapy resistance in a pan-cancer analysis

Despite autophagy modulating tumor immunity in the tumor microenvironment (TME), the immunotherapeutic efficacy and potential mechanism of autophagy signature was not explicit. We manually curated an autophagy gene set and defined a pan-cancer autophagy signature by comparing malignant tissues and normal tissues in The Cancer Genome Atlas (TCGA) cohort. The pan-cancer autophagy signature was derived from T proliferating cells as demonstrated in multiple single-cell RNA sequencing (scRNA-seq) datasets. The pan-cancer autophagy signature could influence the cell-cell interactions in the TME and predict the responsiveness of immune checkpoint inhibitors (ICIs) in the metastatic renal cell carcinoma, non-small cell lung cancer, bladder cancer, and melanoma cohorts. Metabolism inactivation accompanied with dysregulation of autophagy was investigated with transcriptomic and proteomic data. The immunotherapeutic predictive role and mechanism regulation of the autophagy signature was validated in an in-house cohort. Our study provides valuable insights into the mechanisms of ICI resistance.

Plasma cell-free DNA hydroxymethylation profiling reveals anti-PD-1 treatment response and resistance biology in non-small cell lung cancer

BACKGROUND

Treatment with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) can yield durable antitumor responses, yet not all patients respond to ICIs. Current approaches to select patients who may benefit from anti-PD-1 treatment are insufficient. 5-hydroxymethylation (5hmC) analysis of plasma-derived cell-free DNA (cfDNA) presents a novel non-invasive approach for identification of therapy response biomarkers which can tackle challenges associated with tumor biopsies such as tumor heterogeneity and serial sample collection.

METHODS

151 blood samples were collected from 31 patients with non-small cell lung cancer (NSCLC) before therapy started and at multiple time points while on therapy. Blood samples were processed to obtain plasma-derived cfDNA, followed by enrichment of 5hmC-containing cfDNA fragments through biotinylation via a two-step chemistry and binding to streptavidin coated beads. 5hmC-enriched cfDNA and whole genome libraries were prepared in parallel and sequenced to obtain whole hydroxymethylome and whole genome plasma profiles, respectively.

RESULTS

Comparison of on-treatment time point to matched pretreatment samples from same patients revealed that anti-PD-1 treatment induced distinct changes in plasma cfDNA 5hmC profiles of responding patients, as judged by Response evaluation criteria in solid tumors, relative to non-responders. In responders, 5hmC accumulated over genes involved in immune activation such as inteferon (IFN)-γ and IFN-α response, inflammatory response and tumor necrosis factor (TNF)-α signaling, whereas in non-responders 5hmC increased over epithelial to mesenchymal transition genes. Molecular response to anti-PD-1 treatment, as measured by 5hmC changes in plasma cfDNA profiles were observed early on, starting with the first cycle of treatment. Comparison of pretreatment plasma samples revealed that anti-PD-1 treatment response and resistance associated genes can be captured by 5hmC profiling of plasma-derived cfDNA. Furthermore, 5hmC profiling of pretreatment plasma samples was able to distinguish responders from non-responders using T cell-inflamed gene expression profile, which was previously identified by tissue RNA analysis.

CONCLUSIONS

These results demonstrate that 5hmC profiling can identify response and resistance associated biological pathways in plasma-derived cfDNA, offering a novel approach for non-invasive prediction and monitoring of immunotherapy response in NSCLC.

ATM Mutations Associate with Distinct Co-Mutational Patterns and Therapeutic Vulnerabilities in NSCLC

PURPOSE

Ataxia-telangiectasia mutated (ATM) is the most frequently mutated DNA damage repair gene in non-small cell lung cancer (NSCLC). However, the molecular correlates of ATM mutations and their clinical implications have not been fully elucidated.

EXPERIMENTAL DESIGN

Clinicopathologic and genomic data from 26,587 patients with NSCLC from MD Anderson, public databases, and a de-identified nationwide (US-based) NSCLC clinicogenomic database (CGDB) were used to assess the co-mutation landscape, protein expression, and mutational processes in ATM-mutant tumors. We used the CGDB to evaluate ATM-associated outcomes in patients treated with immune checkpoint inhibitors (ICI) with or without chemotherapy, and assessed the effect of ATM loss on STING signaling and chemotherapy sensitivity in preclinical models.

RESULTS

Nonsynonymous mutations in ATM were observed in 11.2% of samples (2,980/26,587) and were significantly associated with mutations in KRAS, but mutually exclusive with EGFR (q < 0.1). KRAS mutational status constrained the ATM co-mutation landscape, with strong mutual exclusivity with TP53 and KEAP1 within KRAS-mutated samples. Those ATM mutations that co-occurred with TP53 were more likely to be missense mutations and associate with high mutational burden, suggestive of non-functional passenger mutations. In the CGDB cohort, dysfunctional ATM mutations associated with improved OS only in patients treated with ICI-chemotherapy, and not ICI alone. In vitro analyses demonstrated enhanced upregulation of STING signaling in ATM knockout cells with the addition of chemotherapy.

CONCLUSIONS

ATM mutations define a distinct subset of NSCLC associated with KRAS mutations, increased TMB, decreased TP53 and EGFR co-occurrence, and potential increased sensitivity to ICIs in the context of DNA-damaging chemotherapy.

Loss of p53 and mutational heterogeneity drives immune resistance in an autochthonous mouse lung cancer model with high tumor mutational burden

The role of tumor mutational burden (TMB) in shaping tumor immunity is a key question that has not been addressable using genetically engineered mouse models (GEMMs) of lung cancer. To induce TMB in lung GEMMs, we expressed an ultra-mutator variant of DNA polymerase-E (POLE)P286R in lung epithelial cells. Introduction of PoleP286R allele into KrasG12D and KrasG12D; p53L/L (KP) models significantly increase their TMB. Immunogenicity and sensitivity to immune checkpoint blockade (ICB) induced by Pole is partially dependent on p53. Corroborating these observations, survival of NSCLC patients whose tumors have TP53truncating mutations is shorter than those with TP53WT with immunotherapy. Immune resistance is in part through reduced antigen presentation and in part due to mutational heterogeneity. Total STING protein levels are elevated in Pole mutated KP tumors creating a vulnerability. A stable polyvalent STING agonist or p53 induction increases sensitivity to immunotherapy offering therapeutic options in these polyclonal tumors.

The role of IFN-γ-signalling in response to immune checkpoint blockade therapy

Treatment with immune checkpoint inhibitors, widely known as immune checkpoint blockade therapy (ICBT), is now the fourth pillar in cancer treatment, offering the chance of durable remission for patients with advanced disease. However, ICBT fails to induce objective responses in most cancer patients with still others progressing after an initial response. It is necessary, therefore, to elucidate the primary and acquired resistance mechanisms to ICBT to improve its efficacy. Here, we highlight the paradoxical role of the cytokine interferon-γ (IFN-γ) in ICBT response: on the one hand induction of IFN-γ signalling in the tumour microenvironment correlates with good ICBT response as it drives the cellular immune responses required for tumour destruction; nonetheless, IFN-γ signalling is implicated in ICBT acquired resistance. We address the negative feedback and immunoregulatory effects of IFN-γ signalling that promote immune evasion and resistance to ICBT and discuss how these can be targeted pharmacologically to restore sensitivity or circumvent resistance.

Reliability of panel-based mutational signatures for immune-checkpoint-inhibition efficacy prediction in non-small cell lung cancer

OBJECTIVES

Mutational signatures (MS) are gaining traction for deriving therapeutic insights for immune checkpoint inhibition (ICI). We asked if MS attributions from comprehensive targeted sequencing assays are reliable enough for predicting ICI efficacy in non-small cell lung cancer (NSCLC).

METHODS

Somatic mutations of m = 126 patients were assayed using panel-based sequencing of 523 cancer-related genes. In silico simulations of MS attributions for various panels were performed on a separate dataset of m = 101 whole genome sequenced patients. Non-synonymous mutations were deconvoluted using COSMIC v3.3 signatures and used to test a previously published machine learning classifier.

RESULTS

The ICI efficacy predictor performed poorly with an accuracy of 0.51-0.09+0.09, average precision of 0.52-0.11+0.11, and an area under the receiver operating characteristic curve of 0.50-0.09+0.10. Theoretical arguments, experimental data, and in silico simulations pointed to false negative rates (FNR) related to panel size. A secondary effect was observed, where deconvolution of small ensembles of point mutations lead to reconstruction errors and misattributions.

CONCLUSION

MS attributions from current targeted panel sequencing are not reliable enough to predict ICI efficacy. We suggest that, for downstream classification tasks in NSCLC, signature attributions be based on whole exome or genome sequencing instead.